• The identifiability for causal effects under a type of assumptions based on conditional independence in a causal model is treated by equation method.

    运用方程组求解的方法来解决一类因果效应可识别充要条件的问题。

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  • Absrtact: Naive Bayesian classifier is a simple and effective classifier, but its conditional independence assumption makes it unable to express the dependence among features.

    摘要朴素贝叶斯分类一种简单高效的分类器,条件独立性假设使无法表示属性问的依赖关系。

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  • If the NB conditional independence assumption actually holds, a Naive Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data.

    倘若条件独立性假设确实满足,朴素贝叶斯分类器将会判别模型,譬如逻辑回归收敛得更快因此需要更少训练数据

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  • Parameter estimation as minimization - intro to method of least squares, introduction to probability theory, conditional and joint probabilities, statistical independence.

    最小化问题估算参数-最小方法介绍机率介绍条件机率联合机率统计无关

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  • Naive Bayes algorithm is a simple and effective classification algorithm. However, its classification performance is affected by its conditional attribute independence assumption.

    朴素贝叶斯算法一种简单高效分类算法,但是条件独立性假设影响分类性能

    youdao

  • Naive Bayes algorithm is a simple and effective classification algorithm. However, its classification performance is affected by its conditional attribute independence assumption.

    朴素贝叶斯算法一种简单高效分类算法,但是条件独立性假设影响分类性能

    youdao

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